This MIKAIA® University app note demonstrates how to quickly and interactively train your own AI using just a few training annotations, all in a matter of minutes. In the app center, select the Segmentation AI Author App, click “+” to...
This MIKAIA® University app note illustrates how to interactively train a new H&E segmentation AI with serial sections, without having to annotate tumor regions. Instead, an IHC epithelial marker (pan-cytokeratin AE1/AE3) is thresholded through...
With the upcoming MIKAIA® 3 release (scheduled for Q1 2026), MIKAIA® will receive a new multi-omics slide alignment module, “MIKAIA® Slide Align“. Based on a 3-phase registration process, the last one being a non-rigid deformation for...
MIKAIA University is the central learning and resources portal for MIKAIA® users. It aims to illustrate how MIKAIA® can be used to make discoveries or automate quantitative analysis in Digital Pathology & Spatial Biology, offering app notes, FAQs, video tutorials, and more.
This article is based on a our presentation “IHC Cell Analysis — More than just Cell Counting: A proposed Workflow” at the European Conference for Digital Pathology (ECDP) 2024 in Vilnius, Lithuania...
MIKAIA® supports various I/O formats, find out which ones. Importable whole-slide-image file formats Format / VendorCommentsOME-TIFFBrightfield and fluorescence. Z-stacks and timelines supported (mutually-exclusive). No...
This MIKAIA® App Note shows how to quantify tumor in proximity to nerve fibers (perineural invasion) in a IHC duplex-stained tissue section, where nerves appear red (antigen: S100) and tumor brown (antigen:...
The first step to creating a supervised Digital Pathology AI is to annotate whole-slide-images. MIKAIA® uses various annotation concepts, and understanding these concepts will make your experience with MIKAIA® much...
About 20 % to 25 % of breast cancers depend on amplification and overexpression of the gene human epidermal growth factor receptor 2 (HER2). The HER2 overexpression status will initially be assessed by...
When designing a new immunohistochemistry (IHC) assay, a quantitative assessment of how it “responds” in different tissues of various organs is insightful and helps optimizing the assay in an objective way...
Tumor cells dynamically interact with their microenvironment to stimulate cancer development, progression, and metastasis. To understand the biology of the tumor-immune interactions, it is essential to identify tumoral...
In this MIKAIA® University application note, we guide you through the analysis of a common use case, coexpression of marker combinations in islets of Langerhans and surrounding tissue in a pancreas 4plex imaged with...
In this MIKAIA® University application note, we guide you through the analysis of a common use case, coexpression of marker combinations in lymphoid follicles and interfollicular tissue in a tonsil 15plex imaged with...
MIKAIA® University Application Note: Analyzing multiplexed immuno fluorescent (mIF) slides MIKAIA® has good support for viewing, annotating and analyzing multi-plexed (aka high-plex, aka hyper-plex) whole-slide images...
© Fraunhofer IIS · 2026
Michaela Benz
Volker Bruns
Nathalie Falk